CN114841228A - 生成用于指定视觉数据集的数据结构 - Google Patents
生成用于指定视觉数据集的数据结构 Download PDFInfo
- Publication number
- CN114841228A CN114841228A CN202210041590.7A CN202210041590A CN114841228A CN 114841228 A CN114841228 A CN 114841228A CN 202210041590 A CN202210041590 A CN 202210041590A CN 114841228 A CN114841228 A CN 114841228A
- Authority
- CN
- China
- Prior art keywords
- visual
- parameters
- visual parameters
- data
- computer
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000000007 visual effect Effects 0.000 title claims abstract description 509
- 230000004438 eyesight Effects 0.000 claims abstract description 175
- 238000010206 sensitivity analysis Methods 0.000 claims abstract description 41
- 238000012549 training Methods 0.000 claims abstract description 38
- 238000013507 mapping Methods 0.000 claims abstract description 35
- 238000000034 method Methods 0.000 claims description 69
- 238000005070 sampling Methods 0.000 claims description 27
- 238000012360 testing method Methods 0.000 claims description 24
- 230000006870 function Effects 0.000 claims description 20
- 239000002131 composite material Substances 0.000 claims description 14
- 238000004590 computer program Methods 0.000 claims description 9
- 238000013528 artificial neural network Methods 0.000 claims description 8
- 238000002474 experimental method Methods 0.000 claims description 4
- 239000011159 matrix material Substances 0.000 claims description 2
- 238000010200 validation analysis Methods 0.000 abstract description 2
- 238000013461 design Methods 0.000 description 13
- 238000001556 precipitation Methods 0.000 description 10
- 230000008569 process Effects 0.000 description 7
- 238000012545 processing Methods 0.000 description 6
- 238000012795 verification Methods 0.000 description 6
- 230000003993 interaction Effects 0.000 description 5
- 238000012986 modification Methods 0.000 description 5
- 230000004048 modification Effects 0.000 description 5
- 230000035945 sensitivity Effects 0.000 description 5
- 238000013459 approach Methods 0.000 description 4
- 238000011161 development Methods 0.000 description 4
- 239000003550 marker Substances 0.000 description 4
- 230000008447 perception Effects 0.000 description 4
- 230000004075 alteration Effects 0.000 description 3
- 230000004313 glare Effects 0.000 description 3
- 238000010801 machine learning Methods 0.000 description 3
- 230000009467 reduction Effects 0.000 description 3
- 238000009877 rendering Methods 0.000 description 3
- 206010047571 Visual impairment Diseases 0.000 description 2
- 238000010521 absorption reaction Methods 0.000 description 2
- 238000000354 decomposition reaction Methods 0.000 description 2
- 230000001419 dependent effect Effects 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 239000000446 fuel Substances 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 230000005855 radiation Effects 0.000 description 2
- 230000002123 temporal effect Effects 0.000 description 2
- 238000000149 argon plasma sintering Methods 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 238000005094 computer simulation Methods 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000010287 polarization Effects 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 238000013139 quantization Methods 0.000 description 1
- 238000007670 refining Methods 0.000 description 1
- 238000002310 reflectometry Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 230000003595 spectral effect Effects 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 210000000857 visual cortex Anatomy 0.000 description 1
- 230000004382 visual function Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computing arrangements using knowledge-based models
- G06N5/01—Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/23—Clustering techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/58—Extraction of image or video features relating to hyperspectral data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
- G06V10/771—Feature selection, e.g. selecting representative features from a multi-dimensional feature space
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
- G06V10/774—Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
- G06V10/776—Validation; Performance evaluation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
- G06V10/778—Active pattern-learning, e.g. online learning of image or video features
- G06V10/7796—Active pattern-learning, e.g. online learning of image or video features based on specific statistical tests
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Evolutionary Computation (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Artificial Intelligence (AREA)
- Software Systems (AREA)
- Multimedia (AREA)
- Databases & Information Systems (AREA)
- Computing Systems (AREA)
- Medical Informatics (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Probability & Statistics with Applications (AREA)
- Mathematical Physics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Evolutionary Biology (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Computational Linguistics (AREA)
- Image Analysis (AREA)
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102021200347.8A DE102021200347A1 (de) | 2021-01-15 | 2021-01-15 | Erzeugen einer datenstruktur zum spezifizieren visueller datensätze |
| DE102021200347.8 | 2021-01-15 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114841228A true CN114841228A (zh) | 2022-08-02 |
Family
ID=82218092
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210041590.7A Pending CN114841228A (zh) | 2021-01-15 | 2022-01-14 | 生成用于指定视觉数据集的数据结构 |
Country Status (3)
| Country | Link |
|---|---|
| US (1) | US20220230072A1 (de) |
| CN (1) | CN114841228A (de) |
| DE (1) | DE102021200347A1 (de) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102021200345A1 (de) * | 2021-01-15 | 2022-07-21 | Robert Bosch Gesellschaft mit beschränkter Haftung | Überprüfung von computervisionsmodellen |
| US11958500B1 (en) * | 2022-05-10 | 2024-04-16 | Ghost Autonomy Inc. | Autonomous vehicle model training and validation using low-discrepancy sequences |
| US11947511B2 (en) | 2022-05-10 | 2024-04-02 | Ghost Autonomy Inc. | Indexing a data corpus to a set of multidimensional points |
| US20240037189A1 (en) * | 2022-07-29 | 2024-02-01 | Plusai, Inc. | Data augmentation by manipulating object contents |
-
2021
- 2021-01-15 DE DE102021200347.8A patent/DE102021200347A1/de active Pending
-
2022
- 2022-01-04 US US17/646,958 patent/US20220230072A1/en active Pending
- 2022-01-14 CN CN202210041590.7A patent/CN114841228A/zh active Pending
Also Published As
| Publication number | Publication date |
|---|---|
| US20220230072A1 (en) | 2022-07-21 |
| DE102021200347A1 (de) | 2022-07-21 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113039563B (zh) | 学习生成用于训练神经网络的合成数据集 | |
| US20220230072A1 (en) | Generating a data structure for specifying visual data sets | |
| CN107636693B (zh) | 针对人工神经网络的相关性分数指派 | |
| Hodges et al. | Single image dehazing using deep neural networks | |
| US11748937B2 (en) | Sub-pixel data simulation system | |
| US12051234B2 (en) | Modifying parameter sets characterising a computer vision model | |
| US11908178B2 (en) | Verification of computer vision models | |
| US20220230418A1 (en) | Computer-implemented method for training a computer vision model | |
| CN117011616B (zh) | 一种图像内容审核方法、装置、存储介质和电子设备 | |
| US20220262103A1 (en) | Computer-implemented method for testing conformance between real and synthetic images for machine learning | |
| US20240046614A1 (en) | Computer-implemented method for generating reliability indications for computer vision | |
| CN117422629B (zh) | 一种实例感知的单目语义场景补全方法、介质及设备 | |
| CN114462486A (zh) | 图像处理模型的训练方法、图像处理方法及相关装置 | |
| Lange et al. | Lopr: Latent occupancy prediction using generative models | |
| US20220237897A1 (en) | Computer-implemented method for analyzing relevance of visual parameters for training a computer vision model | |
| Arvanitis et al. | Cooperative saliency-based obstacle detection and ar rendering for increased situational awareness | |
| Milanov et al. | Method for clustering and identification of objects in laser scanning point clouds using dynamic logic | |
| Kaur et al. | Real Time Object Detection | |
| Palvanov et al. | Development of visibility expectation system based on machine learning | |
| Rodrigues et al. | Change detection based on features invariant to monotonic transforms and spatially constrained matching | |
| He et al. | Uav identification based on improved YOLOv7 under foggy condition | |
| Gizatullin et al. | Automatic car license plate detection based on the image weight model | |
| Roncancio et al. | Ceiling analysis of pedestrian recognition pipeline for an autonomous car application | |
| Wang et al. | Keyframe image processing of semantic 3D point clouds based on deep learning | |
| Neurohr et al. | Requirements on Simulation Systems and Models Posed by a Criticality Analysis for Automated Driving Systems |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |